Decline Of Wild Edible Fruits In Maharashtra’s Tribal Markets: Evidence From Weekly Haat Records 1990-2023
Bibliographic record
Abstract
Weekly haat registers maintained by the Integrated Tribal Development Projects in six major tribal districts of Maharashtra (Nandurbar, Dhule, Nashik, Palghar, Gadchiroli, and Gondia) provide the first systematic, long-term evidence of the collapse of wild edible fruit supply between 1990-91 and 2021-22. Total quantity sold through these official markets has declined from an average of 9 842 tonnes per year in 1990-95 to 2617 tonnes in 2017-22, a fall of 73.4 percent. The number of fruit species regularly appearing in the registers has dropped from 29 to only 9 per season. Among major species, mahua flowers have fallen from 4 126 tonnes to 1 214 tonnes, charoli seeds from 1 348 tonnes to 178 tonnes, amla from 1017 tonnes to 298 tonnes, and jamun from 782 tonnes to 152 tonnes. Real prices paid to collectors (deflated to constant 2022 rupees) have risen between 567 percent (mahua) and 1102 percent (charoli), driven by growing urban and herbal-industry demand, yet actual household cash earnings have declined sharply because collectors now harvest far smaller volumes. The primary drivers are the large-scale replacement of mixed deciduous forests by teak monoculture since the late 1980s, near-total failure of natural regeneration due to uncontrolled grazing and loss of seed-dispersing wildlife, and recent fragmentation caused by highways and mining. The paper concludes that without urgent measures (protection of key species, inclusion of fruits under the Minimum Support Price scheme, and allocation of degraded reserve forest for community-led regeneration), wild edible fruits will soon vanish from both adivasi diets and local economies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".